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Record W2151161319 · doi:10.5539/gjhs.v1n2p85

Review of Barriers to Engaging Black and Minority Ethnic Groups in Physical Activity in the United Kingdom

2009· article· en· W2151161319 on OpenAlexvenueno aff
Sejlo A. Koshoedo, Padam Simkhada

Bibliographic record

VenueGlobal Journal of Health Science · 2009
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
Fundersnot available
KeywordsCINAHLEthnic groupMulticulturalismNarrative reviewMEDLINEHealth equityPromotion (chess)MedicinePopulationGerontologyPsychologyNursingPsychological interventionPolitical scienceEnvironmental healthPublic health

Abstract

fetched live from OpenAlex

Introduction and Objective: The lower physical activity levels in Black and Minority Ethnic (BME) groups as comparedwith general population in the United Kingdom (UK) could relate to barriers to engaging these groups in physicalactivity. Hence, the aim to conduct a review to examine UK primary studies reporting barriers to engaging BME groupsin physical activity. Method: This is a narrative review of literature from 1970 to 2008. The search looked for Englishliterature from five bibliographic databases (MEDLINE, Embase, CINAHL, PsyINFO, Ethnicity and Health). Broadsearch terms ‘physical activity and minority’ were used and views from BME groups were considered in this review.Results & Conclusion: The search yielded 391 studies and 18 were finally included in the review. Our review identified20 barriers clustered among four broad themes of: (a) perceived personal barriers; (b) socio-economic barriers; (c)cultural barriers; and (d) environmental barriers. Overcoming these barriers in these broad areas is important indevelopment of sensitive multicultural health promotion addressing physical inequalities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.692
Threshold uncertainty score0.235

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.101
GPT teacher head0.440
Teacher spread0.339 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations19
Published2009
Admission routes1
Has abstractyes

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